mesh_intro.Rmdhabtools includes a wide range of 3D metrics applicable
to meshes.
Before calculating any metrics, visualize your mesh and make sure that the z orientation is correct, as this may affect some of the calculations.
plot3d(mcap)
Depending on how the mesh was generated (e.g. with the use of a laser scanner), the resolutions (distance between vertices inside the mesh) can vary a lot. This may affect calculations such as fractal dimension. Check the distribution of resolution of your object and if needed, remesh to make the resolution more uniform.
resvec <- Rvcg::vcgMeshres(mcap)[[2]] # vector of resolutions
hist(resvec)
summary(resvec)
#> Min. 1st Qu. Median Mean 3rd Qu. Max.
#> 0.001307 0.005265 0.007003 0.007831 0.009410 0.043981In our example, the mcap object has very variable
distances between vertices. We can solve this issue by remeshing the
object with the Rvcg function vgcUniformRemesh(). Here we
set the resolution (voxelSize) to the minimum distance between points in
the original mesh to ensure we don’t loose details. This choice may be
made on a case-to-case basis. Setting multisample to TRUE improves the
accuracy of distance field computation, but slows down the calculation
so this choice may be defined by computing power and the size of your
object. The remeshed object now has a mean resolution of approximately
the minimum of ‘resvec’. While there will still be some variation in the
obtained distances between vertices, the variation will be much smaller.
An alternative option would be to remesh using an external 3D software
such as blender.
mcap_uniform <- Rvcg::vcgUniformRemesh(mcap, silent = TRUE, multiSample = TRUE, voxelSize = min(resvec), mergeClost = TRUE)
plot3d(mcap_uniform, col = "grey")